Category Archives: CXC Corporate

6/4/16: Apps, Contingent Workforce and U.S. Employment Trends

Here is an interesting chart from the WSJ on the scale of the apps platforms-related Gig-economy employment and the underlying trends in growth on other contingent workforce:

Yes, overall app platform employment is low, as I mentioned in my presentation at the CXC forum on the future of workforce in San Francisco yesterday, but...

The big 'but' here is that overall app platforms-related employment growth is most likely contributing to the weakening of the quality of contingent workforce (in terms of skills, value added and sustainability), not strengthening it, and thus requires more systemic supports and changes in this workforce management and enablement.

More on this later, so stay tuned.

24/1/16: Unobserved Ability and Entrepreneurship

Yesterday, I posted some links relating to non-Cognitive Skills, contextualising these into the Gig-Economy related issues. Here is another interesting study relating to human capital and linking unobserved (and hard to measure) ability to entrepreneurship.

From the policymakers' and indeed investors and other market participants perspective, the question of why do some individuals become entrepreneurs is a salient one.

Identifying the causal relationships between external conditions, systems and policy environments, as well as behavioural and other drivers of entrepreneurship is of great value for setting policies and systems for enhancing the rate of entrepreneurship creation in the economy. A recent paper, titled "Unobserved Ability and Entrepreneurship" by Deepak Hegde and Justin Tumlinson (Ifo Institute at the University of Munich, April 20, 2015) attempts to answer to key questions surrounding the formation of entrepreneurship, namely:

  1. Why do individuals become entrepreneurs? and
  2. When do they succeed? 

The authors "develop a model in which individuals use pedigree (e.g., educational qualifications) as a signal to convince employers of their unobserved ability. However, this signal is imperfect…" So far - logical: upon attaining a level of education, and controlling for quality of that education (complexity of degree programme, subject matter, quality of awarding institution, duration of studies, attainment of grades etc), a graduate acquire more than a sum of knowledge and skills attached to the degree. They also acquire a signal that can be communicated to their potential employer that conveys they lateen (hidden) abilities; attitude toward work, aptitude, ability to work in teams, ability to work on complex systems of tasks etc.

Problem is - the signal is noisy. For example, a graduate with 4.0 GPA from a second tier university can have better potential abilities than a graduate with 3.7 GPA from a first tier ranked university. But that information may not be clearly evident to the potential employer. As the result, there can be a large mismatch between what an applicant thinks their ability is and what their CV signals to the potential employer.

In the paper, theoretical model delivers a clear cut outcome (emphasis mine): "…individuals who correctly believe their ability is greater than their pedigree conveys to employers, choose entrepreneurship. Since ability, not pedigree, matters for productivity, entrepreneurs earn more than employees of the same pedigree."

The authors use US and UK data to test their model prediction (again, emphasis is mine): "Our empirical analysis of two separate nationally representative longitudinal samples of individuals residing in the US and the UK supports the model’s predictions that

  • (A) Entrepreneurs have higher ability than employees of the same pedigree, 
  • (B) Employees have better pedigree than entrepreneurs of the same ability, and 
  • (C) Entrepreneurs earn more, on average, than employees of the same pedigree, and their earnings display higher variance."

Point C clearly indicates that entrepreneurs earn positive risk premium for effectively (correctly, on average) betting on their ability over their pedigree. In other words, the take chance in themselves and, on average, win. The real question, however, is why exactly do their earnings exhibit higher variance - is it due to distributional effects across the entrepreneurs by their ability, or is it due to risk-adjusted returns being similar, or is it due to exogenous shocks to entrepreneurs incomes (e.g. tax system-induced or contractually-structured)?

These are key questions we do not yet address in research sufficiently enough to allow us to understand better what the Gig-Economy and entrepreneurship in modern day setting imply in terms of aggregate consumption, investment, household investment and decision making by entire household in terms of labour supply, educational choices (for parents and children), etc.

As some might say... it's complicated...

23/1/16: Non-Cognitive Human Capital

In my 2011 paper on the role of Human Capital in the emerging post-ICT Revolution economy, human capital will simultaneously:

  1. Play increasingly more important role in determining returns to technical and processes innovation;
  2. Become more diverse in its nature - or more diversified - spanning measurable and unmeasurable skills, traits, knowledge, attitudes to risk and innovation, capabilities etc.; and
  3. Form the critical foundation of entrepreneurship and core employment base in the so-called Type 1 Gig-Economy - economy based on contingent workforce compered of highly skilled, highly value-additive professionals.

An interesting paper relating to the matter, especially to the last point, is a recent IZA Working paper (October 2015) titled “Non-Cognitive Skills as Human Capital” by Shelly Lundberg.

Per Lundberg: “In recent years, a large number of studies have shown strong positive associations between so-called “non-cognitive skills” — a broad and ill-defined category of metrics encompassing personality, socio-emotional skills, and behaviors — and economic success and wellbeing. These skills appear to be malleable early in life, raising the possibility of interventions that can decrease inequality and enhance economic productivity.”

Lundberg discusses “the extensive practical and conceptual barriers to using non-cognitive skill measures in studies of economic growth, as well as to developing or evaluating relevant policies. …There is a lack of general agreement on what non-cognitive skills are and how to measure them across developmental stages, and the reliance on behavioral measures of skills ensures that both skill indicators themselves, and their payoffs, will be context-dependent. The empirical examples show that indicators of adolescent skills have strong associations with educational attainment, but not subsequent labor market outcomes, and illustrate some problems in interpreting apparent skill gaps across demographic groups.”

From the Gig-Economy point of view, development of all (cognitive and non-cognitive) skills requires time and resources. In traditional workplace setting - of old variety - some of these resources and time allocations are supported / subsidised by employers (e.g. gym memberships, formal paid time off, formal paid career breaks, formal 'team building' activities, actual employer-paid training and education, employer-supported psychological wellness programmes for employees, and so on). In a Gig-Economy setting, these are not available, generally, to contingent workers.

Aside from having impact on contingent workforce skills and human capital, there are more 'trivial' considerations that should be put to analysis. Take, for example, health and psychological well-being. If a contingent workforce using company fails to assure the latter for its contingent workers, who is liable for any damages caused by over-worked, over-stressed, psychologically unwell contingent worker to the company clients?

Again, setting aside humanitarian, social and personal considerations, this question has implications for businesses using contingent workers:

  • Insurance costs and coverage for businesses;
  • Legal costs and coverage for business;
  • Reputational risks for businesses;
  • Counter-party risks for businesses; and so on

In a world where there is no such thing as a free lunch, Gig-Economy based companies should seriously consider how they are going to deal with potential costs of disruption from the Gig-Economy type of employment to life-cycle work practices and financial wellbeing of their contingent workers.

Note: More on the subject of non-cognitive skills and human capital:

14/1/16: Push or Pull: Entrepreneurship Among Older Households

Recently, I highlighted some of the potential problems relating to the less stable nature of the Gig Economy employment, including the longer-term pressures on life-cycle savings and pensions, as well as health care provision (you can see my discussion here: and my slides here:

Mainstream economics has been lagging behind this trend, with little research on the long-term sustainability of the Gig Economy employment. Thus, it is quite heartening to see some related, albeit tangentially, research coming up.

One example is a very interesting study on entrepreneurship amongst the U.S. older households. Weller, Christian E. and Wenger, Jeffrey B. and Lichtenstein, Benyamin and Arcand, Carolyn, paper titled "Push or Pull: What Explains Growing Entrepreneurship Among Older Households?" (November 30, 2015: does what it says: it looks at both push and pull factors for entrepreneurship and self-employment amongst older households.

Per authors (italics are mine): "Older households need to save more money for retirement, possibly by working longer. [Which is a pull factor for self-employment and  entrepreneurship]. But, the same labor market pressures that have made it harder for people to save, such as increasingly unstable labor markets, have also made it more difficult for people to work longer as wage and salary employees. [Which is a push factor toward self-employment and entrepreneurship].

Self-employment hence may have become an increasingly attractive alternative option for older households.

Entrepreneurship among older households has indeed grown faster than wage and salary employment, especially since the late 1990s.

But, this growth, rather than reflecting rising economic pressures, may have been the result of growing financial strengths – fewer financial constraints and more access to income diversification through capital income from rising wealth. Our empirical analysis finds little support for the hypothesis that growing economic pressures have contributed to increasing entrepreneurship. Instead, our results suggest that the growth of older entrepreneurship is coincident with increasing access to income diversification, especially from dividend and interest income. We also find some tentative evidence that access to Social Security and other annuity benefits increasingly correlate with self-employment. Greater access to interest and dividend income follows in part from more wealth and improved access to Social Security may reflect relatively strong labor market experience in the past."

This is an interesting result, because it is based on older households' access to:

  1. Income from savings and wealth, including assets wealth; and
  2. Income from retirement.
In the Gig Economy, both are likely to be compressed due to higher income volatility (and thus rising precautionary savings), tax incidences that impose liability with a lag (inducing higher income uncertainty), and lower earnings (due to lack of paid vacations, maternity/paternity and sick leave). In some cases, e.g. countries like Ireland, there is also an explicit income tax penalty for the self-employed (via both lower standard deductions and higher tax rates, such as those under the USC). All of which implies reduced access to income from retirement in the future, lower savings and wealth (including through inheritance). 

Subsequently, the current cohort of older entrepreneurs and self-employed may exhibit exactly the opposite drivers for their post-retirement employment choices than today's younger cohorts. And that matters because entrepreneurship and self-employment that start with push factors (e.g. necessity of life and constraints of the labour markets) is less successful than entrepreneurship and self-employment that start with pull factors.